System and method for adaptive cruise control with proximate vehicle detection

ABSTRACT

A system and method for adaptive cruise control with proximate vehicle detection are disclosed. The example embodiment can be configured for: receiving input object data from a subsystem of a host vehicle, the input object data including distance data and velocity data relative to detected target vehicles; detecting the presence of any target vehicles within a sensitive zone in front of the host vehicle, to the left of the host vehicle, and to the right of the host vehicle; determining a relative speed and a separation distance between each of the detected target vehicles relative to the host vehicle; and generating a velocity command to adjust a speed of the host vehicle based on the relative speeds and separation distances between the host vehicle and the detected target vehicles to maintain a safe separation between the host vehicle and the target vehicles.

PRIORITY PATENT APPLICATIONS

This is a continuation of U.S. patent application Ser. No. 15/806,127,titled, “System and Method For Adaptive Cruise Control With ProximateVehicle Detection”, filed Nov. 7, 2017, and published as U.S.2019-0001977, which in turn is a continuation-in-part (CIP) of U.S.patent application Ser. No. 15/640,516 titled “System and Method ForAdaptive Cruise Control For Low Speed Following,” filed Jul. 1, 2017,and published as U.S. 2019-0001976. The entire disclosure of thereferenced patent applications are considered part of the disclosure ofthe present application and are hereby incorporated by reference hereintheir entirety.

COPYRIGHT NOTICE

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the U.S. Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever. The following notice applies to the disclosure hereinand to the drawings that form a part of this document: Copyright2016-2017, TuSimple, All Rights Reserved.

TECHNICAL FIELD

This patent document pertains generally to tools (systems, apparatuses,methodologies, computer program products, etc.) for vehicle controlsystems, cruise control systems, and autonomous driving systems, andmore particularly, but not by way of limitation, to a system and methodfor adaptive cruise control with proximate vehicle detection.

BACKGROUND

An autonomous vehicle is often configured to follow a trajectory basedon a computed driving path. However, when variables such as obstaclesare present on the driving path, the autonomous vehicle must performcontrol operations so that the controlled vehicle may be safely drivenby changing the speed or the driving path to avoid the obstacles. Inmany cases, data from cameras can be used to detect obstacles (e.g.other vehicles) in the path. In other cases, radar or LIDAR data can beused. LIDAR is a surveying method that measures distance to a target byilluminating that target with a pulsed laser light and measuring thereflected pulses with a sensor. Differences in laser return times andwavelengths can then be used to make digital representations of thetarget.

Such a vehicle-mounted radar or LIDAR apparatus can be used withautomatic cruise control systems, which operate to detect a lead vehicle(e.g., a vehicle positioned ahead and in the same lane as the controlledvehicle). Conventional cruise control systems are configured to causethe controlled vehicle to maintain a constant speed or a speed thatkeeps constant the following distance to the lead vehicle. However,traditional cruise control systems that only consider the speed of thecontrolled vehicle or the distance between the lead vehicle and thefollowing vehicle might fail to react quickly enough to changes in theoperation of the lead vehicle, thereby causing an unsafe separationbetween the two vehicles. Additionally, traditional cruise controlsystems fail to detect and consider the actions of other vehicles in theproximity of the controlled vehicle.

SUMMARY

A system and method for adaptive cruise control with proximate vehicledetection are disclosed herein. Specifically, the present disclosurerelates to an adaptive cruise control (ACC) system and method thatallows a host vehicle (e.g., an autonomous or controlled vehicle) toautonomously and safely perform cruise control operations with proximatevehicles positioned in front of or to either side of the host vehicle.In an example embodiment, both the relative separation distance and therelative velocity between the vehicles are taken into account in orderto calculate and control the host vehicle's desired velocity and headingat each time step. In contrast to conventional vehicle cruise controlsystems, the example embodiments are configured to detect and determinea speed, separation distance, and heading of other vehicles in theproximity of the host vehicle for better adaptive cruise control.

BRIEF DESCRIPTION OF THE DRAWINGS

The various embodiments are illustrated by way of example, and not byway of limitation, in the figures of the accompanying drawings in which:

FIG. 1 illustrates a block diagram of an example ecosystem in which anadaptive cruise control module of an example embodiment can beimplemented;

FIG. 2 illustrates an example scenario with two vehicles in a typicalconfiguration where one vehicle leads and another vehicle follows;

FIGS. 3 and 4 illustrate the components of the adaptive cruise controlmodule of an example embodiment;

FIG. 5 illustrates the components of a control mechanism for low speedfollowing for the adaptive cruise control module of an exampleembodiment;

FIG. 6 is a process flow diagram illustrating an example embodiment of amethod for adaptive cruise control for low speed following;

FIG. 7 illustrates a traditional adaptive cruise control (ACC)technology that focuses on the closest front or leading vehicle in thecurrent lane (e.g., the same lane as the host vehicle) as the targetvehicle;

FIG. 8 illustrates an example embodiment that uses three vehiclepositions as potential ACC target vehicles: a front or leading vehiclein the same current lane as the host vehicle, and possibly two otherproximate vehicles in an ACC sensitive zone in the neighboring lanes oneach side of the host vehicle;

FIG. 9 illustrates an example embodiment that can compute thedifferentials (Δd) of the separation distances between the each of thetarget vehicles and the host vehicle over time and can also compute thedifferentials (Δv) of the speeds of the target vehicles relative to thehost vehicle over time;

FIGS. 10 and 11 illustrate plots of the host vehicle velocity over timeas a target vehicle merges into a lane in which the host vehicle isdriving;

FIG. 12 is a flow diagram that illustrates an example embodiment of asystem and method for adaptive cruise control with proximate vehicledetection;

FIG. 13 is another flow diagram that illustrates an example embodimentof a system and method for adaptive cruise control with proximatevehicle detection; and

FIG. 14 shows a diagrammatic representation of machine in the exampleform of a computer system within which a set of instructions whenexecuted may cause the machine to perform any one or more of themethodologies discussed herein.

DETAILED DESCRIPTION

In the following description, for purposes of explanation, numerousspecific details are set forth in order to provide a thoroughunderstanding of the various embodiments. It will be evident, however,to one of ordinary skill in the art that the various embodiments may bepracticed without these specific details.

As described in various example embodiments, a system and method foradaptive cruise control with proximate vehicle detection are describedherein. An example embodiment disclosed herein can be used in thecontext of an in-vehicle control system 150 in a vehicle ecosystem 101as shown in FIG. 1. In one example embodiment, an in-vehicle controlsystem 150 with an adaptive cruise control module 200 resident in avehicle 105 can be configured like the architecture and ecosystem 101illustrated in FIG. 1. However, it will be apparent to those of ordinaryskill in the art that the adaptive cruise control module 200 describedand claimed herein can be implemented, configured, and used in a varietyof other applications and systems as well.

Referring now to FIG. 1, a block diagram illustrates an exampleecosystem 101 in which an in-vehicle control system 150 and an adaptivecruise control module 200 of an example embodiment can be implemented.These components are described in more detail below. Ecosystem 101includes a variety of systems and components that can generate and/ordeliver one or more sources of information/data and related services tothe in-vehicle control system 150 and the adaptive cruise control module200, which can be installed in the vehicle 105. For example, a camerainstalled in the vehicle 105, as one of the devices of vehiclesubsystems 140, can generate image and timing data that can be receivedby the in-vehicle control system 150. The in-vehicle control system 150and an image processing module executing therein can receive this imageand timing data input. The image processing module can extract objectdata from the image and timing data to identify objects in the proximityof the vehicle 105. Additionally, a LIDAR sensor installed in thevehicle 105, as another one of the devices of vehicle subsystems 140,can generate distance data as point clouds that can be received by thein-vehicle control system 150. The in-vehicle control system 150 and aLIDAR data processing module executing therein can receive this distancedata and point cloud input. The LIDAR data processing module cangenerate distance data relative to objects detected in the proximity ofthe vehicle 105. The in-vehicle control system 150 can process theobject image data and object distance data of detected objects togenerate a position and velocity for each proximate object near theautonomous vehicle 105. As described in more detail below, the adaptivecruise control module 200 can use the position and velocity for eachproximate object to manage the speed and distance of the vehicle 105relative to a lead vehicle (e.g., a detected proximate object). Vehiclecontrol or command signals generated by the adaptive cruise controlmodule 200 can be used by an autonomous vehicle control subsystem, asanother one of the subsystems of vehicle subsystems 140, to maintain thevehicle 105 at a speed and on a path that does not intersect with thepaths of the proximate objects, including the lead vehicle. Theautonomous vehicle control subsystem, for example, can use the vehiclecontrol or command signals to safely and efficiently control andnavigate the vehicle 105 through a real world driving environment whileavoiding obstacles and safely controlling the vehicle.

In an example embodiment as described herein, the in-vehicle controlsystem 150 can be in data communication with a plurality of vehiclesubsystems 140, all of which can be resident in a user's vehicle 105. Avehicle subsystem interface 141 is provided to facilitate datacommunication between the in-vehicle control system 150 and theplurality of vehicle subsystems 140. The in-vehicle control system 150can be configured to include a data processor 171 to execute theadaptive cruise control module 200 for processing vehicle distance andvelocity data received from one or more of the vehicle subsystems 140.The data processor 171 can be combined with a data storage device 172 aspart of a computing system 170 in the in-vehicle control system 150. Thedata storage device 172 can be used to store data, processingparameters, weight coefficients, and data processing instructions. Aprocessing module interface 165 can be provided to facilitate datacommunications between the data processor 171 and the adaptive cruisecontrol module 200. In various example embodiments, a plurality ofprocessing modules, configured similarly to adaptive cruise controlmodule 200, can be provided for execution by data processor 171. Asshown by the dashed lines in FIG. 1, the adaptive cruise control module200 can be integrated into the in-vehicle control system 150, optionallydownloaded to the in-vehicle control system 150, or deployed separatelyfrom the in-vehicle control system 150.

The in-vehicle control system 150 can be configured to receive ortransmit data from/to a wide-area network 120 and network resources 122connected thereto. An in-vehicle web-enabled device 130 and/or a usermobile device 132 can be used to communicate via network 120. Aweb-enabled device interface 131 can be used by the in-vehicle controlsystem 150 to facilitate data communication between the in-vehiclecontrol system 150 and the network 120 via the in-vehicle web-enableddevice 130. Similarly, a user mobile device interface 133 can be used bythe in-vehicle control system 150 to facilitate data communicationbetween the in-vehicle control system 150 and the network 120 via theuser mobile device 132. In this manner, the in-vehicle control system150 can obtain real-time access to network resources 122 via network120. The network resources 122 can be used to obtain processing modulesfor execution by data processor 171, data content to train internalneural networks, system parameters, or other data.

The ecosystem 101 can include a wide area data network 120. The network120 represents one or more conventional wide area data networks, such asthe Internet, a cellular telephone network, satellite network, pagernetwork, a wireless broadcast network, gaming network, WiFi network,peer-to-peer network, Voice over IP (VoIP) network, etc. One or more ofthese networks 120 can be used to connect a user or client system withnetwork resources 122, such as websites, servers, central control sites,or the like. The network resources 122 can generate and/or distributedata, which can be received in vehicle 105 via in-vehicle web-enableddevices 130 or user mobile devices 132. The network resources 122 canalso host network cloud services, which can support the functionalityused to compute or assist in processing object input or object inputanalysis. Antennas can serve to connect the in-vehicle control system150 and the adaptive cruise control module 200 with the data network 120via cellular, satellite, radio, or other conventional signal receptionmechanisms. Such cellular data networks are currently available (e.g.,Verizon™, AT&T™, T-Mobile™, etc.). Such satellite-based data or contentnetworks are also currently available (e.g., SiriusXM™, HughesNet™,etc.). The conventional broadcast networks, such as AM/FM radionetworks, pager networks, UHF networks, gaming networks, WiFi networks,peer-to-peer networks, Voice over IP (VoIP) networks, and the like arealso well-known. Thus, as described in more detail below, the in-vehiclecontrol system 150 and the adaptive cruise control module 200 canreceive web-based data or content via an in-vehicle web-enabled deviceinterface 131, which can be used to connect with the in-vehicleweb-enabled device receiver 130 and network 120. In this manner, thein-vehicle control system 150 and the adaptive cruise control module 200can support a variety of network-connectable in-vehicle devices andsystems from within a vehicle 105.

As shown in FIG. 1, the in-vehicle control system 150 and the adaptivecruise control module 200 can also receive data, processing controlparameters, and training content from user mobile devices 132, which canbe located inside or proximately to the vehicle 105. The user mobiledevices 132 can represent standard mobile devices, such as cellularphones, smartphones, personal digital assistants (PDA's), MP3 players,tablet computing devices (e.g., iPad™), laptop computers, CD players,and other mobile devices, which can produce, receive, and/or deliverdata, object processing control parameters, and content for thein-vehicle control system 150 and the adaptive cruise control module200. As shown in FIG. 1, the mobile devices 132 can also be in datacommunication with the network cloud 120. The mobile devices 132 cansource data and content from internal memory components of the mobiledevices 132 themselves or from network resources 122 via network 120.Additionally, mobile devices 132 can themselves include a GPS datareceiver, accelerometers, WiFi triangulation, or other geo-locationsensors or components in the mobile device, which can be used todetermine the real-time geo-location of the user (via the mobile device)at any moment in time. In any case, the in-vehicle control system 150and the adaptive cruise control module 200 in data communicationtherewith can receive data from the mobile devices 132 as shown in FIG.1.

Referring still to FIG. 1, the example embodiment of ecosystem 101 caninclude vehicle operational subsystems 140. For embodiments that areimplemented in a vehicle 105, many standard vehicles include operationalsubsystems, such as electronic control units (ECUs), supportingmonitoring/control subsystems for the engine, brakes, transmission,electrical system, emissions system, interior environment, and the like.For example, data signals communicated from the vehicle operationalsubsystems 140 (e.g., ECUs of the vehicle 105) to the in-vehicle controlsystem 150 via vehicle subsystem interface 141 may include informationabout the state of one or more of the components or subsystems of thevehicle 105. In particular, the data signals, which can be communicatedfrom the vehicle operational subsystems 140 to a Controller Area Network(CAN) bus of the vehicle 105, can be received and processed by thein-vehicle control system 150 via vehicle subsystem interface 141.Embodiments of the systems and methods described herein can be used withsubstantially any mechanized system that uses a CAN bus or similar datacommunications bus as defined herein, including, but not limited to,industrial equipment, boats, trucks, machinery, or automobiles; thus,the term “vehicle” as used herein can include any such mechanizedsystems. Embodiments of the systems and methods described herein canalso be used with any systems employing some form of network datacommunications; however, such network communications are not required.

Referring still to FIG. 1, the example embodiment of ecosystem 101, andthe vehicle operational subsystems 140 therein, can include a variety ofvehicle subsystems in support of the operation of vehicle 105. Ingeneral, the vehicle 105 may take the form of a car, truck, motorcycle,bus, boat, airplane, helicopter, lawn mower, earth mover, snowmobile,aircraft, recreational vehicle, amusement park vehicle, farm equipment,construction equipment, tram, golf cart, train, and trolley, forexample. Other vehicles are possible as well. The vehicle 105 may beconfigured to operate fully or partially in an autonomous mode. Forexample, the vehicle 105 may control itself while in the autonomousmode, and may be operable to determine a current state of the vehicleand its environment, determine a predicted behavior of at least oneother vehicle in the environment, determine a confidence level that maycorrespond to a likelihood of the at least one other vehicle to performthe predicted behavior, and control the vehicle 105 based on thedetermined information. While in autonomous mode, the vehicle 105 may beconfigured to operate without human interaction.

The vehicle 105 may include various vehicle subsystems such as a vehicledrive subsystem 142, vehicle sensor subsystem 144, vehicle controlsubsystem 146, and occupant interface subsystem 148. As described above,the vehicle 105 may also include the in-vehicle control system 150, thecomputing system 170, and the adaptive cruise control module 200. Thevehicle 105 may include more or fewer subsystems and each subsystemcould include multiple elements. Further, each of the subsystems andelements of vehicle 105 could be interconnected. Thus, one or more ofthe described functions of the vehicle 105 may be divided up intoadditional functional or physical components or combined into fewerfunctional or physical components. In some further examples, additionalfunctional and physical components may be added to the examplesillustrated by FIG. 1.

The vehicle drive subsystem 142 may include components operable toprovide powered motion for the vehicle 105. In an example embodiment,the vehicle drive subsystem 142 may include an engine or motor,wheels/tires, a transmission, an electrical subsystem, and a powersource. The engine or motor may be any combination of an internalcombustion engine, an electric motor, steam engine, fuel cell engine,propane engine, or other types of engines or motors. In some exampleembodiments, the engine may be configured to convert a power source intomechanical energy. In some example embodiments, the vehicle drivesubsystem 142 may include multiple types of engines or motors. Forinstance, a gas-electric hybrid car could include a gasoline engine andan electric motor. Other examples are possible.

The wheels of the vehicle 105 may be standard tires. The wheels of thevehicle 105 may be configured in various formats, including a unicycle,bicycle, tricycle, or a four-wheel format, such as on a car or a truck,for example. Other wheel geometries are possible, such as thoseincluding six or more wheels. Any combination of the wheels of vehicle105 may be operable to rotate differentially with respect to otherwheels. The wheels may represent at least one wheel that is fixedlyattached to the transmission and at least one tire coupled to a rim ofthe wheel that could make contact with the driving surface. The wheelsmay include a combination of metal and rubber, or another combination ofmaterials. The transmission may include elements that are operable totransmit mechanical power from the engine to the wheels. For thispurpose, the transmission could include a gearbox, a clutch, adifferential, and drive shafts. The transmission may include otherelements as well. The drive shafts may include one or more axles thatcould be coupled to one or more wheels. The electrical system mayinclude elements that are operable to transfer and control electricalsignals in the vehicle 105. These electrical signals can be used toactivate lights, servos, electrical motors, and other electricallydriven or controlled devices of the vehicle 105. The power source mayrepresent a source of energy that may, in full or in part, power theengine or motor. That is, the engine or motor could be configured toconvert the power source into mechanical energy. Examples of powersources include gasoline, diesel, other petroleum-based fuels, propane,other compressed gas-based fuels, ethanol, fuel cell, solar panels,batteries, and other sources of electrical power. The power source couldadditionally or alternatively include any combination of fuel tanks,batteries, capacitors, or flywheels. The power source may also provideenergy for other subsystems of the vehicle 105.

The vehicle sensor subsystem 144 may include a number of sensorsconfigured to sense information about an environment or condition of thevehicle 105. For example, the vehicle sensor subsystem 144 may includean inertial measurement unit (IMU), a Global Positioning System (GPS)transceiver, a RADAR unit, a laser range finder/LIDAR unit, and one ormore cameras or image capture devices. The vehicle sensor subsystem 144may also include sensors configured to monitor internal systems of thevehicle 105 (e.g., an O₂ monitor, a fuel gauge, an engine oiltemperature, etc.). Other sensors are possible as well. One or more ofthe sensors included in the vehicle sensor subsystem 144 may beconfigured to be actuated separately or collectively in order to modifya position, an orientation, or both, of the one or more sensors.

The IMU may include any combination of sensors (e.g., accelerometers andgyroscopes) configured to sense position and orientation changes of thevehicle 105 based on inertial acceleration. The GPS transceiver may beany sensor configured to estimate a geographic location of the vehicle105. For this purpose, the GPS transceiver may include areceiver/transmitter operable to provide information regarding theposition of the vehicle 105 with respect to the Earth. The RADAR unitmay represent a system that utilizes radio signals to sense objectswithin the local environment of the vehicle 105. In some embodiments, inaddition to sensing the objects, the RADAR unit may additionally beconfigured to sense the speed and the heading of the objects proximateto the vehicle 105. The laser range finder or LIDAR unit may be anysensor configured to sense objects in the environment in which thevehicle 105 is located using lasers or other distance measuringequipment. In an example embodiment, the laser range finder/LIDAR unitmay include one or more laser sources, a laser scanner, and one or moredetectors, among other system components. The laser range finder/LIDARunit could be configured to operate in a coherent (e.g., usingheterodyne detection) or an incoherent detection mode. The cameras mayinclude one or more devices configured to capture a plurality of imagesof the environment of the vehicle 105. The cameras may be still imagecameras or motion video cameras.

The vehicle control system 146 may be configured to control operation ofthe vehicle 105 and its components. Accordingly, the vehicle controlsystem 146 may include various elements such as a steering unit, athrottle, a brake unit, a navigation unit, and an autonomous controlunit.

The steering unit may represent any combination of mechanisms that maybe operable to adjust the heading of vehicle 105. The throttle may beconfigured to control, for instance, the operating speed of the engineand, in turn, control the speed of the vehicle 105. The brake unit caninclude any combination of mechanisms configured to decelerate thevehicle 105. The brake unit can use friction to slow the wheels in astandard manner. In other embodiments, the brake unit may convert thekinetic energy of the wheels to electric current. The brake unit maytake other forms as well. The navigation unit may be any systemconfigured to determine a driving path or route for the vehicle 105. Thenavigation unit may additionally be configured to update the drivingpath dynamically while the vehicle 105 is in operation. In someembodiments, the navigation unit may be configured to incorporate datafrom the adaptive cruise control module 200, the GPS transceiver, andone or more predetermined maps so as to determine the driving path forthe vehicle 105. The autonomous control unit may represent a controlsystem configured to identify, evaluate, and avoid or otherwisenegotiate potential obstacles in the environment of the vehicle 105. Ingeneral, the autonomous control unit may be configured to control thevehicle 105 for operation without a driver or to provide driverassistance in controlling the vehicle 105. In some embodiments, theautonomous control unit may be configured to incorporate data from theadaptive cruise control module 200, the GPS transceiver, the RADAR, theLIDAR, the cameras, and other vehicle subsystems to determine thedriving path or trajectory for the vehicle 105. The vehicle controlsystem 146 may additionally or alternatively include components otherthan those shown and described.

Occupant interface subsystems 148 may be configured to allow interactionbetween the vehicle 105 and external sensors, other vehicles, othercomputer systems, and/or an occupant or user of vehicle 105. Forexample, the occupant interface subsystems 148 may include standardvisual display devices (e.g., plasma displays, liquid crystal displays(LCDs), touchscreen displays, heads-up displays, or the like), speakersor other audio output devices, microphones or other audio input devices,navigation interfaces, and interfaces for controlling the internalenvironment (e.g., temperature, fan, etc.) of the vehicle 105.

In an example embodiment, the occupant interface subsystems 148 mayprovide, for instance, means for a user/occupant of the vehicle 105 tointeract with the other vehicle subsystems. The visual display devicesmay provide information to a user of the vehicle 105. The user interfacedevices can also be operable to accept input from the user via atouchscreen. The touchscreen may be configured to sense at least one ofa position and a movement of a user's finger via capacitive sensing,resistance sensing, or a surface acoustic wave process, among otherpossibilities. The touchscreen may be capable of sensing finger movementin a direction parallel or planar to the touchscreen surface, in adirection normal to the touchscreen surface, or both, and may also becapable of sensing a level of pressure applied to the touchscreensurface. The touchscreen may be formed of one or more translucent ortransparent insulating layers and one or more translucent or transparentconducting layers. The touchscreen may take other forms as well.

In other instances, the occupant interface subsystems 148 may providemeans for the vehicle 105 to communicate with devices within itsenvironment. The microphone may be configured to receive audio (e.g., avoice command or other audio input) from a user of the vehicle 105.Similarly, the speakers may be configured to output audio to a user ofthe vehicle 105. In one example embodiment, the occupant interfacesubsystems 148 may be configured to wirelessly communicate with one ormore devices directly or via a communication network. For example, awireless communication system could use 3G cellular communication, suchas CDMA, EVDO, GSM/GPRS, or 4G cellular communication, such as WiMAX orLTE. Alternatively, the wireless communication system may communicatewith a wireless local area network (WLAN), for example, using WIFI®. Insome embodiments, the wireless communication system 146 may communicatedirectly with a device, for example, using an infrared link, BLUETOOTH®,or ZIGBEE®. Other wireless protocols, such as various vehicularcommunication systems, are possible within the context of thedisclosure. For example, the wireless communication system may includeone or more dedicated short range communications (DSRC) devices that mayinclude public or private data communications between vehicles and/orroadside stations.

Many or all of the functions of the vehicle 105 can be controlled by thecomputing system 170. The computing system 170 may include at least onedata processor 171 (which can include at least one microprocessor) thatexecutes processing instructions stored in a non-transitory computerreadable medium, such as the data storage device 172. The computingsystem 170 may also represent a plurality of computing devices that mayserve to control individual components or subsystems of the vehicle 105in a distributed fashion. In some embodiments, the data storage device172 may contain processing instructions (e.g., program logic) executableby the data processor 171 to perform various functions of the vehicle105, including those described herein in connection with the drawings.The data storage device 172 may contain additional instructions as well,including instructions to transmit data to, receive data from, interactwith, or control one or more of the vehicle drive subsystem 140, thevehicle sensor subsystem 144, the vehicle control subsystem 146, and theoccupant interface subsystems 148.

In addition to the processing instructions, the data storage device 172may store data such as pre-configured processing parameters, weightcoefficients, training data, roadway maps, and path information, amongother information. Such information may be used by the vehicle 105 andthe computing system 170 during the operation of the vehicle 105 in theautonomous, semi-autonomous, and/or manual modes.

The vehicle 105 may include a user interface for providing informationto or receiving input from a user or occupant of the vehicle 105. Theuser interface may control or enable control of the content and thelayout of interactive images that may be displayed on a display device.Further, the user interface may include one or more input/output deviceswithin the set of occupant interface subsystems 148, such as the displaydevice, the speakers, the microphones, or a wireless communicationsystem.

The computing system 170 may control the function of the vehicle 105based on inputs received from various vehicle subsystems (e.g., thevehicle drive subsystem 140, the vehicle sensor subsystem 144, and thevehicle control subsystem 146), as well as from the occupant interfacesubsystem 148. For example, the computing system 170 may use input fromthe vehicle control system 146 in order to control the steering unit toavoid an obstacle detected by the vehicle sensor subsystem 144 andfollow a path or trajectory and speed generated with the assistance ofdata and commands from the adaptive cruise control module 200. In anexample embodiment, the computing system 170 can be operable to providecontrol over many aspects of the vehicle 105 and its subsystems.

Although FIG. 1 shows various components of vehicle 105, e.g., vehiclesubsystems 140, computing system 170, data storage device 172, andadaptive cruise control module 200, as being integrated into the vehicle105, one or more of these components could be mounted or associatedseparately from the vehicle 105. For example, data storage device 172could, in part or in full, exist separate from the vehicle 105. Thus,the vehicle 105 could be provided in the form of device elements thatmay be located separately or together. The device elements that make upvehicle 105 could be communicatively coupled together in a wired orwireless fashion.

Additionally, other data and/or content (denoted herein as ancillarydata) can be obtained from local and/or remote sources by the in-vehiclecontrol system 150 as described above. The ancillary data can be used toaugment, modify, or train the operation of the adaptive cruise controlmodule 200 based on a variety of factors including, the context in whichthe user is operating the vehicle (e.g., the location of the vehicle,the specified destination, direction of travel, speed, the time of day,the status of the vehicle, etc.), and a variety of other data obtainablefrom the variety of sources, local and remote, as described herein.

In a particular embodiment, the in-vehicle control system 150 and theadaptive cruise control module 200 can be implemented as in-vehiclecomponents of vehicle 105. In various example embodiments, thein-vehicle control system 150 and the adaptive cruise control module 200in data communication therewith can be implemented as integratedcomponents or as separate components. In an example embodiment, thesoftware components of the in-vehicle control system 150 and/or theadaptive cruise control module 200 can be dynamically upgraded,modified, and/or augmented by use of the data connection with the mobiledevices 132 and/or the network resources 122 via network 120. Thein-vehicle control system 150 can periodically query a mobile device 132or a network resource 122 for updates or updates can be pushed to thein-vehicle control system 150.

Referring now to FIG. 2, a diagram illustrates an example scenario withtwo vehicles in a typical configuration 202 where one vehicle leads andanother vehicle follows. In the example shown, a following vehicle 203is shown and configured to include the in-vehicle control system 150 asdescribed herein. Another vehicle 204 is positioned in the same lane andin front of the following vehicle 203 and separated by a distanced_(actual). As such, the vehicle 204 is denoted as the lead vehicle. Inthe example shown, the following vehicle 203 is traveling at a velocityof V_(following). The lead vehicle is traveling at a velocity ofV_(lead). The distance d_(actual) between the following vehicle 203 andthe lead vehicle 204 can be measured at any point in time using theradar or LIDAR sensors in the following vehicle 203 as described above.Similarly, the velocities V_(following) and V_(lead) can be measured ina similar manner. The challenge with the configuration shown in FIG. 2is to either maintain a constant or desired distance d_(actual) betweenthe lead vehicle 204 and the following vehicle 203 or to cause thevelocity V_(following) of the following vehicle 203 to match thevelocity V_(lead) of the lead vehicle 204. Thus, it is important todetermine a command velocity V_(cmd) to control the following vehicle203 to conform to the desired distance or velocity. In this manner, asafe separation between the lead vehicle 204 and the following vehicle203 can be maintained. As described in more detail below, the relativevelocity of the autonomous vehicle 203 and the lead vehicle 204 ascontrolled by the example embodiment is considered to allow theautonomous vehicle 203 to respond in a way that is similar to humandrivers' defensive driving behavior when following a lead vehicle.

Referring now to FIG. 3, a diagram illustrates the components of anadaptive cruise control system 201 with the adaptive cruise controlmodule 200 of an example embodiment. In the example embodiment, theadaptive cruise control module 200 can be configured to include a datacollection module 173 and a velocity command generation module 175. Asdescribed in more detail below, the data collection module 173 and thevelocity command generation module 175 serve to enable generation of avelocity command, V_(cmd), 220, which is the velocity at which afollowing vehicle (e.g., the controlled autonomous vehicle) is commandedto drive. The input object data 210 can include image data from acamera, which can be processed by an image processing module to identifyproximate objects (e.g., moving vehicles, dynamic agents, or otherobjects in the proximate vicinity of the vehicle 105). The input objectdata 210 can also include object distance data or point clouds from aLIDAR sensor, which can be processed by a LIDAR data processing moduleto determine a distance and velocity of each proximate object relativeto the vehicle 105. The data collection module 173 and the velocitycommand generation module 175 can be configured as software modulesexecuted by the data processor 171 of the in-vehicle control system 150.The modules 173 and 175 of the adaptive cruise control module 200 canreceive the input object data 210 and produce the velocity command,V_(cmd), 220, which is the velocity at which a following vehicle iscommanded to drive, based on the distance and velocity of each proximateobject from the input object data 210. The velocity command, V_(cmd),220 can be used by the autonomous control subsystem of the vehiclecontrol subsystem 146 to more efficiently and safely control the vehicle105. As part of the generation of the velocity command, V_(cmd), 220,the data collection module 173 and the velocity command generationmodule 175 can be configured to work with cruise control weightcoefficients and configuration parameters 174, which can be used tocustomize and fine tune the operation of the adaptive cruise controlmodule 200. The cruise control weight coefficients and configurationparameters 174 can be stored in a memory 172 of the in-vehicle controlsystem 150.

In the example embodiment, the adaptive cruise control module 200 can beconfigured to include an interface with the in-vehicle control system150, as shown in FIG. 1, through which the adaptive cruise controlmodule 200 can send and receive data as described herein. Additionally,the adaptive cruise control module 200 can be configured to include aninterface with the in-vehicle control system 150 and/or other ecosystem101 subsystems through which the adaptive cruise control module 200 canreceive ancillary data from the various data sources described above. Asdescribed above, the adaptive cruise control module 200 can also beimplemented in systems and platforms that are not deployed in a vehicleand not necessarily used in or with a vehicle.

In an example embodiment as shown in FIG. 3, the adaptive cruise controlmodule 200 can be configured to include the data collection module 173and the velocity command generation module 175, as well as otherprocessing modules not shown for clarity. Each of these modules can beimplemented as software, firmware, or other logic components executingor activated within an executable environment of the adaptive cruisecontrol module 200 operating within or in data communication with thein-vehicle control system 150. Each of these modules of an exampleembodiment is described in more detail below in connection with thefigures provided herein.

System and Method for Adaptive Cruise Control for Defensive Driving

A system and method for adaptive cruise control for low speed followingis disclosed herein. Specifically, the example embodiments describedherein relate to an adaptive cruise control system and method thatallows a controlled vehicle to autonomously and safely follow behind alead vehicle positioned in front of the autonomous vehicle. In anexample embodiment, both the relative distance and relative velocitybetween the two vehicles are taken into account in order to calculateand control the autonomous vehicle's desired distance or velocity ateach time step. In an example embodiment, the velocity commandgeneration module 175 can use the following expression to generate thevelocity command, V_(cmd), 220:

V _(cmd) =V _(lead) +W ₁(d _(actual) −d _(desired))+W ₂(V _(lead) −V_(following))

Where:

-   -   V_(cmd) is the velocity at which the following vehicle (e.g.,        the controlled autonomous vehicle) is commanded to drive;    -   V_(lead) is the measured velocity of the lead vehicle positioned        in front of the following vehicle (e.g., in front of the        controlled autonomous vehicle);    -   W₁ is a weight coefficient for configuring the significance of        the distance differential;    -   d_(actual) is the actual measured distance between the lead        vehicle and the following vehicle at any point in time;    -   d_(desired) is the desired distance to maintain between the lead        vehicle and the following vehicle;    -   W₂ is a weight coefficient for configuring the significance of        the velocity differential; and    -   V_(following) is the velocity of the following vehicle (e.g.,        the controlled autonomous vehicle).

In an example embodiment, the adaptive cruise control module 200 can beconfigured to use the data collection module 173 and the velocitycommand generation module 175 to generate the velocity command, V_(cmd),220, which is the velocity at which a following vehicle (e.g., thecontrolled autonomous vehicle) is commanded to drive to maintain adesired distance or velocity. The usage of the expression describedabove by the velocity command generation module 175 is described in moredetail in connection with FIG. 4.

FIG. 4 illustrates the components of the adaptive cruise control module200 of an example embodiment. As shown, the adaptive cruise controlmodule 200 can be configured to include a data collection module 173 anda velocity command generation module 175. The adaptive cruise controlmodule 200, and the data collection module 173 therein, can receiveinput object data 210 from one or more of the vehicle sensor subsystems144, including one or more cameras and one or more LIDAR sensors. Theinput object data 210 can include image data from a video streamgenerated by an image generating device, such as a camera. The inputobject data 210 can also include distance data from a distance measuringdevice, such as a LIDAR sensor device. The image data from the inputobject data 210 can be processed by an image data processing module toidentify proximate vehicles or other objects (e.g., moving vehicles,dynamic agents, or other objects in the proximate vicinity of thevehicle 105). For example, a process of semantic segmentation and/orobject detection can be used to process the image data and identifyobjects in the images. The input object data 210 can include distancedata from the distance measuring device, such as a LIDAR sensor device.The distance data can be represented as point clouds from the LIDAR. Thedistance data can be used to measure the distances from the vehicle 105to each of the potential proximate objects with a high degree ofprecision. The distance data can also be used to measure the velocitiesof the proximate objects relative to the vehicle 105. The data relatedto the identified objects and corresponding distance and velocitymeasurements can be received by the data collection module 173. Inparticular, the data collection module 173 can receive datacorresponding to the distance, d_(actual) 211 between a lead vehicle 204and a following vehicle 203. The data collection module 173 can alsoreceive data corresponding to the lead vehicle 204 velocity V_(lead) andthe following vehicle 203 velocity V_(following) 212.

Referring still to FIG. 4, the velocity command generation module 175can receive the distance data 211 and velocity data 212 from the datacollection module 173. The velocity command generation module 175 can bepre-configured with a parameter d_(desired), which represents thedesired distance that should be maintained between the lead vehicle 204and the following vehicle 203. The parameter d_(desired) can be auser-configurable parameter. The velocity command generation module 175can also be pre-configured with cruise control weight coefficients W₁and W₂. W₁ is a user-configurable weight coefficient for configuring thesignificance of the distance differential between the actual distanced_(actual) and a desired distance d_(desired). W₂ is a user-configurableweight coefficient for configuring the significance of the velocitydifferential between the velocity V_(lead) of the lead vehicle 204 andthe velocity V_(following) of the following vehicle 203.

As shown in FIG. 4, the velocity command generation module 175 cancompute the product of the distance weight coefficient W₁ and thedistance differential between the actual distance d_(actual) and adesired distance d_(desired) between the following vehicle 203 and thelead vehicle 204. The velocity command generation module 175 can alsocompute the product of the velocity weight coefficient W₂ and thevelocity differential between the velocity V_(lead) of the lead vehicle204 and the velocity V_(following) of the following vehicle 203. Theseproducts are combined or summed with the lead vehicle velocity V_(lead)in block 218. As a result of the computation in block 218, the velocitycommand generation module 175 can generate data indicative of a velocitycommand, V_(cmd), 220, which is the velocity at which the followingvehicle 203 (e.g., the controlled autonomous vehicle) is commanded todrive to maintain a desired distance or velocity relative to the leadvehicle 204. The velocity command, V_(cmd), 220 can be used by thein-vehicle control system 150 to control the speed of the autonomousvehicle to conform with the speed corresponding to the velocity command.

System and Method for Adaptive Cruise Control for Low Speed Following

FIG. 5 illustrates the components of a control mechanism for low speedfollowing for the adaptive cruise control module of an exampleembodiment. In the example embodiment shown in FIG. 5, a speed orvelocity command can be generated by the adaptive cruise control module200 or other control mechanisms of the autonomous vehicle 105. The speedcommand represents the desired speed at which the autonomous vehicle 105should be traveling. The various vehicle subsystems 140, as describedabove, can measure or determine the actual measured speed of the vehicleusing one or more sensor systems. The speed command and the measuredspeed can be provided as inputs to a difference engine 505. Thedifference engine 505 can provide as an output a value or signalcorresponding to the difference between the speed command and themeasured speed. This difference or speed error can be provided as aninput to a dynamic gain module 510. In a particular embodiment, ameasured speed can also be provided as an input to the dynamic gainmodule 510. The details of the processing performed by the dynamic gainmodule 510 are described below.

In an example embodiment, the measured speed can also be provided as aninput to a speed derivative module 515. The speed derivative module 515can compute a derivative of the measured speed using conventionaltechniques to produce a measured acceleration. The measured accelerationcan be provided as an input to a difference engine 520. The differenceengine 520 can provide as an output a value or signal corresponding tothe difference between an acceleration command and the measuredacceleration. This difference or acceleration error can be provided asan input to a throttle pedal control module, which can control theoperation of the vehicle's throttle to achieve the desired speed. Theacceleration command can also be provided as an input to a brake pedalcontrol module, which can control the operation of the vehicle's brakingsystem.

Referring again to the dynamic gain module 510, an example embodimentprovides a dynamic and variable gain mechanism, which is applied to thespeed error output from the difference engine 505 to produce theacceleration command. In contrast to conventional control systems thatuse a constant or fixed gain, the example embodiments disclosed hereinprovide a dynamic and variable gain, which is applied to produce theacceleration command. As a result, the dynamic gain produced by thedynamic gain module 510 provides a more responsive control system undera wide variety of vehicle operating conditions, including speed. Forexample, a conventional fixed gain control system may be configured towork well at typical vehicle high cruise speeds. However, these fixedgain control systems are either under-responsive or overly-responsive atslow speeds. As a result, conventional cruise control systems do notoperate efficiently at slow speeds, such as the conditions encounteredin a traffic jam. In response to this problem, the example embodimentsdescribed herein provide the dynamic gain module 510, which provides adynamic and variable gain to appropriately adjust the accelerationcommand for all vehicle speed ranges. In a particular embodiment, themeasured speed can be provided as an input to the dynamic gain module510. The dynamic gain module 510 can adjust the output dynamic gain as afunction of the measured speed. In other alternative embodiment, otherinputs can be provided to the dynamic gain module 510. For example, thespeed command value, the measured acceleration, or other dynamic inputscan be provided to the dynamic gain module 510. These inputs can be usedby the dynamic gain module 510 to dynamically adjust the output dynamicgain as a function of these inputs. As a result, the dynamic gainprovided by the dynamic gain module 510 can enable the cruise controlsystems as described herein to operate efficiently, even at slow speeds,such as the conditions encountered in a traffic jam or low speedfollowing.

Referring now to FIG. 6, a flow diagram illustrates an exampleembodiment of a system and method 1000 for adaptive cruise control forlow speed following. The example embodiment can be configured for:receiving input object data from a subsystem of an autonomous vehicle,the input object data including distance data and velocity data relativeto a lead vehicle (processing block 1010); generating a weighteddistance differential corresponding to a weighted difference between anactual distance between the autonomous vehicle and the lead vehicle anda desired distance between the autonomous vehicle and the lead vehicle(processing block 1020); generating a weighted velocity differentialcorresponding to a weighted difference between a velocity of theautonomous vehicle and a velocity of the lead vehicle (processing block1030); combining the weighted distance differential and the weightedvelocity differential with the velocity of the lead vehicle to produce avelocity command for the autonomous vehicle (processing block 1040);adjusting the velocity command using a dynamic gain (processing block1050); and controlling the autonomous vehicle to conform to the adjustedvelocity command (processing block 1060).

System and Method for Adaptive Cruise Control with Proximate VehicleDetection

A system and method for adaptive cruise control with proximate vehicledetection are disclosed herein. Specifically, the present disclosurerelates to an adaptive cruise control (ACC) system and method thatallows a host vehicle (e.g., an autonomous or controlled vehicle) toautonomously and safely perform cruise control operations with proximatevehicles positioned in front of or to either side of the host vehicle.In an example embodiment, both the relative separation distance and therelative velocity between the vehicles are taken into account in orderto calculate and control the host vehicle's desired velocity and headingat each time step. In contrast to conventional vehicle cruise controlsystems, the example embodiments are configured to detect and determinea speed, separation distance, and heading of other vehicles in theproximity of the host vehicle for better adaptive cruise control.

Referring now to FIG. 7, traditional adaptive cruise control (ACC)technologies typically focus on the closest front or leading vehicle inthe current lane (e.g., the same lane as the host vehicle) as the targetvehicle and use an objective function to maintain a separation distanceand minimize speed differences with the target vehicle. One challengefor this method as shown in FIG. 7 is when a vehicle (merging vehicleshown in FIG. 7) merges in from a neighboring lane or a highway on-rampwith a lower speed (v) and a shorter separation distance (d) than a safepredefined separation distance between the host vehicle and the mergingvehicle. In this situation, the host vehicle has limited options toavoid collision. One viable option to avoid collision is to reduce thespeed of the host vehicle to avoid the merging vehicle. However,traditional ACC systems will typically not vary the speed of the hostvehicle under these conditions, which can cause an unsafe drivingsituation.

In the various example embodiments described herein, the adaptive cruisecontrol system 201 and the velocity command generation module 175therein can be configured to detect a plurality of target vehicles inthe vicinity of (proximate to) the host vehicle. As described above, theadaptive cruise control module 200, and the data collection module 173therein, can receive input object data 210 from one or more of thevehicle sensor subsystems 144, including one or more cameras and one ormore LIDAR sensors. The input object data 210 can include image datafrom a video stream generated by an image generating device, such as acamera. The input object data 210 can also include distance data from adistance measuring device, such as a LIDAR sensor device. The image datafrom the input object data 210 can be processed by an image dataprocessing module to identify proximate vehicles or other objects (e.g.,moving vehicles, dynamic agents, or other objects in the proximatevicinity of the vehicle 105). In an example embodiment, these proximatevehicles can be used as target vehicles in the processing performed bythe velocity command generation module 175.

Referring now to FIG. 8, an example embodiment can use three vehiclepositions as potential ACC target vehicles: a front or leading vehiclein the same current lane as the host vehicle, and possibly two otherproximate vehicles in an ACC sensitive zone in the neighboring lanes oneach side of the host vehicle. By detecting the target vehicles in thefront and to the sides of the host vehicle, the velocity commandgeneration module 175 of the example embodiments can adjust the speed ofthe host vehicle based on the relative speeds and separation distancesbetween the host vehicle and the target vehicles. As a result, theexample embodiments can configure the velocity command generation module175 to modify the velocity command 220 output from the ACC 201 to causethe host vehicle to maintain a safe speed and separation distance from atarget vehicle that may merge into the lane in which the host vehicle isdriving. Additionally, the velocity command generation module 175 can beconfigured to cause the host vehicle to stay out of the blind spots ofany proximate vehicles based on the relative speeds and separationdistances between the host vehicle and the target vehicles. Thus, thevarious example embodiments can increase the safety of an autonomousvehicle encountering merging situations with other proximate vehicles.

Referring still to FIG. 8, the host vehicle is shown in proximity withthree other target vehicles: a front vehicle with a separation distanced_(f) from the host vehicle, a left front vehicle with a separationdistance d_(l) from the host vehicle, and a right front vehicle with aseparation distance d_(r) from the host vehicle. Again, as describedabove, the adaptive cruise control module 200 can detect these proximatevehicles using the input object data 210 and determine the distance,speed, and heading of the proximate vehicles. In the example embodiment,a sensitive zone can be defined as a region around the host vehiclewithin pre-defined distance thresholds. The pre-defined distancethresholds can be defined separately for the area in front of the hostvehicle, the area to the left of the host vehicle, and the area to theright of the host vehicle. Thus, as shown in FIG. 8, a front or leadingvehicle that is positioned at a distance that is less than or equal tothe pre-defined distance threshold for the area in front of the hostvehicle (e.g., d_(f)<=the front pre-defined threshold) becomes a targetvehicle for consideration by the velocity command generation module 175as described in more detail below. Similarly, a left front vehicle thatis positioned at a distance that is less than or equal to thepre-defined distance threshold for the area to the left of the hostvehicle (e.g., d₁<=the left front pre-defined threshold) also becomes atarget vehicle for consideration by the velocity command generationmodule 175. Finally, as also shown in FIG. 8, a right front vehicle thatis positioned at a distance that is less than or equal to thepre-defined distance threshold for the area to the right of the hostvehicle (e.g., d_(r)<=the right front pre-defined threshold) alsobecomes a target vehicle for consideration by the velocity commandgeneration module 175. As such, any proximate vehicles detected to bewithin the sensitive zone of the host vehicle can be target vehicles forconsideration by the velocity command generation module 175. In variousexample embodiments, the front pre-defined threshold, the left frontpre-defined threshold, and the right front pre-defined threshold can bethe same distance. However, in an example embodiment, the frontpre-defined threshold is typically longer or greater than the left frontpre-defined threshold and the right front pre-defined threshold to givegreater consideration to the leading vehicle in the same lane as thehost vehicle. Additionally, the right front pre-defined threshold can begreater than the left front pre-defined threshold to give greaterconsideration to target vehicles on the right that are more likely to bemerging from the right in countries or regions where vehicles drive onthe right side of the roadway. Typically, the left and right pre-definedthresholds are configured to be shorter or less than the frontpre-defined threshold. It will be apparent to those of ordinary skill inthe art in view of the disclosure herein that the front pre-definedthreshold, the left front pre-defined threshold, and the right frontpre-defined threshold can be appropriately configured for the drivingenvironment in which the ACC 201 will operate.

Referring now to FIG. 9, once the velocity command generation module 175detects the target vehicles in the front and to the sides of the hostvehicle as described above, the velocity command generation module 175of the example embodiments can determine the speed and the separationdistance between each of the target vehicles relative to the hostvehicle. Additionally, because the speed (V_(h)) and position of thehost vehicle can be readily determined from information obtained fromthe vehicle subsystems 140, the velocity command generation module 175can compute the differentials (Δd) of the separation distances betweenthe each of the target vehicles and the host vehicle over time. Thevelocity command generation module 175 can also compute thedifferentials (Δv) of the speeds of the target vehicles relative to thehost vehicle over time.

In the example shown in FIG. 9, a target vehicle (merging vehicle) hasbeen detected at time to operating at speed V_(m) in the sensitive zoneas within the right front pre-defined threshold relative to the hostvehicle operating at speed V_(h). Given the differential (Δd) of theseparation distance and the differential (Δv) of the speed V_(m) of thetarget vehicle relative to the speed V_(h) of the host vehicle, thevelocity command generation module 175 can compute the predictedposition and speed of the target vehicle (merging vehicle) at a futurepoint in time (e.g., t₁ . . . t_(n)). Because the velocity commandgeneration module 175 can also obtain the speed and position of the hostvehicle at any point in time, the velocity command generation module 175can determine if the predicted position or distance of the targetvehicle will encroach within a pre-defined safety boundary around thehost vehicle. If the velocity command generation module 175 determinesthat a target vehicle's predicted position or distance will encroachwithin the pre-defined safety boundary around the host vehicle, thevelocity command generation module 175 can adjust the speed of the hostvehicle based on the relative speeds and separation distances betweenthe host vehicle and the target vehicles. As a result, the exampleembodiments can configure the velocity command generation module 175 tomodify the velocity command 220 output from the ACC 201 to cause thehost vehicle to adjust its speed to maintain a safe speed and separationdistance from any of the detected target vehicles that may merge intothe lane in which the host vehicle is driving. Because each of thetarget vehicles detected to be in proximity to the host vehicle willhave different positions (e.g., distances) and may be operating atdifferent speeds relative to the host vehicle, the velocity commandgeneration module 175 can process the different parameters of eachtarget vehicle separately and then generate a recommended speed for thehost vehicle that maintains separation from each of the target vehicles.

FIGS. 10 and 11 illustrate plots of the host vehicle velocity over timeas a target vehicle merges into a lane in which the host vehicle isdriving. Using the position (e.g., distance) and speed of the mergingtarget vehicle, the velocity command generation module 175 in the hostvehicle can anticipate the merge of the target vehicle at an earlierpoint and can adjust the speed of the host vehicle more gradually inboth amplitude and duration to maintain a safe separation between thehost vehicle and the merging target vehicle. FIG. 10 illustrates theresults produced by conventional methods using techniques that do notdetect proximate merging vehicles. As shown, the velocity of the hostvehicle experiences steeper and more abrupt speed variations for alonger period of time as the target vehicle begins to merge into thelane occupied by the host vehicle. In contrast, FIG. 11 illustrates theresults produced by the adaptive cruise control techniques disclosed forvarious example embodiments herein that do detect proximate mergingvehicles. As shown, the velocity of the host vehicle experiences lessabrupt speed variations for a shorter period of time as the targetvehicle begins to merge into the lane occupied by the host vehicle.

Referring now to FIG. 12, a flow diagram illustrates an exampleembodiment of a system and method for adaptive cruise control withproximate vehicle detection. The example embodiment can be configured toinitially detect the presence of any target vehicles within a sensitivezone in front of a host vehicle, to the left of the host vehicle, and tothe right of the host vehicle. The velocity command generation module175 can be configured to determine the relative speed and the separationdistance between each of the detected target vehicles relative to thehost vehicle. The velocity command generation module 175 can beconfigured to generate a velocity command 220 to adjust the speed of thehost vehicle based on the relative speeds and separation distancesbetween the host vehicle and the target vehicles to maintain a safeseparation between the host vehicle and the target vehicles.

Referring now to FIG. 13, another flow diagram illustrates an exampleembodiment of a system and method 2000 for adaptive cruise control withproximate vehicle detection. The example embodiment can be configuredfor: receiving input object data from a subsystem of a host vehicle, theinput object data including distance data and velocity data relative todetected target vehicles (processing block 2010); detecting the presenceof any target vehicles within a sensitive zone in front of the hostvehicle, to the left of the host vehicle, and to the right of the hostvehicle (processing block 2020); determining a relative speed and aseparation distance between each of the detected target vehiclesrelative to the host vehicle (processing block 2030); and generating avelocity command to adjust a speed of the host vehicle based on therelative speeds and separation distances between the host vehicle andthe detected target vehicles to maintain a safe separation between thehost vehicle and the target vehicles (processing block 2040).

As used herein and unless specified otherwise, the term “mobile device”includes any computing or communications device that can communicatewith the in-vehicle control system 150 and/or the adaptive cruisecontrol module 200 described herein to obtain read or write access todata signals, messages, or content communicated via any mode of datacommunications. In many cases, the mobile device 130 is a handheld,portable device, such as a smart phone, mobile phone, cellulartelephone, tablet computer, laptop computer, display pager, radiofrequency (RF) device, infrared (IR) device, global positioning device(GPS), Personal Digital Assistants (PDA), handheld computers, wearablecomputer, portable game console, other mobile communication and/orcomputing device, or an integrated device combining one or more of thepreceding devices, and the like. Additionally, the mobile device 130 canbe a computing device, personal computer (PC), multiprocessor system,microprocessor-based or programmable consumer electronic device, networkPC, diagnostics equipment, a system operated by a vehicle 105manufacturer or service technician, and the like, and is not limited toportable devices. The mobile device 130 can receive and process data inany of a variety of data formats. The data format may include or beconfigured to operate with any programming format, protocol, or languageincluding, but not limited to, JavaScript, C++, iOS, Android, etc.

As used herein and unless specified otherwise, the term “networkresource” includes any device, system, or service that can communicatewith the in-vehicle control system 150 and/or the adaptive cruisecontrol module 200 described herein to obtain read or write access todata signals, messages, or content communicated via any mode ofinter-process or networked data communications. In many cases, thenetwork resource 122 is a data network accessible computing platform,including client or server computers, websites, mobile devices,peer-to-peer (P2P) network nodes, and the like. Additionally, thenetwork resource 122 can be a web appliance, a network router, switch,bridge, gateway, diagnostics equipment, a system operated by a vehicle105 manufacturer or service technician, or any machine capable ofexecuting a set of instructions (sequential or otherwise) that specifyactions to be taken by that machine. Further, while only a singlemachine is illustrated, the term “machine” can also be taken to includeany collection of machines that individually or jointly execute a set(or multiple sets) of instructions to perform any one or more of themethodologies discussed herein. The network resources 122 may includeany of a variety of providers or processors of network transportabledigital content. Typically, the file format that is employed isExtensible Markup Language (XML), however, the various embodiments arenot so limited, and other file formats may be used. For example, dataformats other than Hypertext Markup Language (HTML)/XML or formats otherthan open/standard data formats can be supported by various embodiments.Any electronic file format, such as Portable Document Format (PDF),audio (e.g., Motion Picture Experts Group Audio Layer 3—MP3, and thelike), video (e.g., MP4, and the like), and any proprietary interchangeformat defined by specific content sites can be supported by the variousembodiments described herein.

The wide area data network 120 (also denoted the network cloud) usedwith the network resources 122 can be configured to couple one computingor communication device with another computing or communication device.The network may be enabled to employ any form of computer readable dataor media for communicating information from one electronic device toanother. The network 120 can include the Internet in addition to otherwide area networks (WANs), cellular telephone networks, metro-areanetworks, local area networks (LANs), other packet-switched networks,circuit-switched networks, direct data connections, such as through auniversal serial bus (USB) or Ethernet port, other forms ofcomputer-readable media, or any combination thereof. The network 120 caninclude the Internet in addition to other wide area networks (WANs),cellular telephone networks, satellite networks, over-the-air broadcastnetworks, AM/FM radio networks, pager networks, UHF networks, otherbroadcast networks, gaming networks, WiFi networks, peer-to-peernetworks, Voice Over IP (VoIP) networks, metro-area networks, local areanetworks (LANs), other packet-switched networks, circuit-switchednetworks, direct data connections, such as through a universal serialbus (USB) or Ethernet port, other forms of computer-readable media, orany combination thereof. On an interconnected set of networks, includingthose based on differing architectures and protocols, a router orgateway can act as a link between networks, enabling messages to be sentbetween computing devices on different networks. Also, communicationlinks within networks can typically include twisted wire pair cabling,USB, Firewire, Ethernet, or coaxial cable, while communication linksbetween networks may utilize analog or digital telephone lines, full orfractional dedicated digital lines including T1, T2, T3, and T4,Integrated Services Digital Networks (ISDNs), Digital User Lines (DSLs),wireless links including satellite links, cellular telephone links, orother communication links known to those of ordinary skill in the art.Furthermore, remote computers and other related electronic devices canbe remotely connected to the network via a modem and temporary telephonelink.

The network 120 may further include any of a variety of wirelesssub-networks that may further overlay stand-alone ad-hoc networks, andthe like, to provide an infrastructure-oriented connection. Suchsub-networks may include mesh networks, Wireless LAN (WLAN) networks,cellular networks, and the like. The network may also include anautonomous system of terminals, gateways, routers, and the likeconnected by wireless radio links or wireless transceivers. Theseconnectors may be configured to move freely and randomly and organizethemselves arbitrarily, such that the topology of the network may changerapidly. The network 120 may further employ one or more of a pluralityof standard wireless and/or cellular protocols or access technologiesincluding those set forth herein in connection with network interface712 and network 714 described in the figures herewith.

In a particular embodiment, a mobile device 132 and/or a networkresource 122 may act as a client device enabling a user to access anduse the in-vehicle control system 150 and/or the adaptive cruise controlmodule 200 to interact with one or more components of a vehiclesubsystem. These client devices 132 or 122 may include virtually anycomputing device that is configured to send and receive information overa network, such as network 120 as described herein. Such client devicesmay include mobile devices, such as cellular telephones, smart phones,tablet computers, display pagers, radio frequency (RF) devices, infrared(IR) devices, global positioning devices (GPS), Personal DigitalAssistants (PDAs), handheld computers, wearable computers, gameconsoles, integrated devices combining one or more of the precedingdevices, and the like. The client devices may also include othercomputing devices, such as personal computers (PCs), multiprocessorsystems, microprocessor-based or programmable consumer electronics,network PC's, and the like. As such, client devices may range widely interms of capabilities and features. For example, a client deviceconfigured as a cell phone may have a numeric keypad and a few lines ofmonochrome LCD display on which only text may be displayed. In anotherexample, a web-enabled client device may have a touch sensitive screen,a stylus, and a color LCD display screen in which both text and graphicsmay be displayed. Moreover, the web-enabled client device may include abrowser application enabled to receive and to send wireless applicationprotocol messages (WAP), and/or wired application messages, and thelike. In one embodiment, the browser application is enabled to employHyperText Markup Language (HTML), Dynamic HTML, Handheld Device MarkupLanguage (HDML), Wireless Markup Language (WML), WMLScript, JavaScript™,EXtensible HTML (xHTML), Compact HTML (CHTML), and the like, to displayand send a message with relevant information.

The client devices may also include at least one client application thatis configured to receive content or messages from another computingdevice via a network transmission. The client application may include acapability to provide and receive textual content, graphical content,video content, audio content, alerts, messages, notifications, and thelike. Moreover, the client devices may be further configured tocommunicate and/or receive a message, such as through a Short MessageService (SMS), direct messaging (e.g., Twitter), email, MultimediaMessage Service (MIMS), instant messaging (IM), internet relay chat(IRC), mIRC, Jabber, Enhanced Messaging Service (EMS), text messaging,Smart Messaging, Over the Air (OTA) messaging, or the like, betweenanother computing device, and the like. The client devices may alsoinclude a wireless application device on which a client application isconfigured to enable a user of the device to send and receiveinformation to/from network resources wirelessly via the network.

The in-vehicle control system 150 and/or the adaptive cruise controlmodule 200 can be implemented using systems that enhance the security ofthe execution environment, thereby improving security and reducing thepossibility that the in-vehicle control system 150 and/or the adaptivecruise control module 200 and the related services could be compromisedby viruses or malware. For example, the in-vehicle control system 150and/or the adaptive cruise control module 200 can be implemented using aTrusted Execution Environment, which can ensure that sensitive data isstored, processed, and communicated in a secure way.

FIG. 14 shows a diagrammatic representation of a machine in the exampleform of a computing system 700 within which a set of instructions whenexecuted and/or processing logic when activated may cause the machine toperform any one or more of the methodologies described and/or claimedherein. In alternative embodiments, the machine operates as a standalonedevice or may be connected (e.g., networked) to other machines. In anetworked deployment, the machine may operate in the capacity of aserver or a client machine in server-client network environment, or as apeer machine in a peer-to-peer (or distributed) network environment. Themachine may be a personal computer (PC), a laptop computer, a tabletcomputing system, a Personal Digital Assistant (PDA), a cellulartelephone, a smartphone, a web appliance, a set-top box (STB), a networkrouter, switch or bridge, or any machine capable of executing a set ofinstructions (sequential or otherwise) or activating processing logicthat specify actions to be taken by that machine. Further, while only asingle machine is illustrated, the term “machine” can also be taken toinclude any collection of machines that individually or jointly executea set (or multiple sets) of instructions or processing logic to performany one or more of the methodologies described and/or claimed herein.

The example computing system 700 can include a data processor 702 (e.g.,a System-on-a-Chip (SoC), general processing core, graphics core, andoptionally other processing logic) and a memory 704, which cancommunicate with each other via a bus or other data transfer system 706.The mobile computing and/or communication system 700 may further includevarious input/output (I/O) devices and/or interfaces 710, such as atouchscreen display, an audio jack, a voice interface, and optionally anetwork interface 712. In an example embodiment, the network interface712 can include one or more radio transceivers configured forcompatibility with any one or more standard wireless and/or cellularprotocols or access technologies (e.g., 2nd (2G), 2.5, 3rd (3G), 4th(4G) generation, and future generation radio access for cellularsystems, Global System for Mobile communication (GSM), General PacketRadio Services (GPRS), Enhanced Data GSM Environment (EDGE), WidebandCode Division Multiple Access (WCDMA), LTE, CDMA2000, WLAN, WirelessRouter (WR) mesh, and the like). Network interface 712 may also beconfigured for use with various other wired and/or wirelesscommunication protocols, including TCP/IP, UDP, SIP, SMS, RTP, WAP,CDMA, TDMA, UMTS, UWB, WiFi, WiMax, Bluetooth™, IEEE 802.11x, and thelike. In essence, network interface 712 may include or support virtuallyany wired and/or wireless communication and data processing mechanismsby which information/data may travel between a computing system 700 andanother computing or communication system via network 714.

The memory 704 can represent a machine-readable medium on which isstored one or more sets of instructions, software, firmware, or otherprocessing logic (e.g., logic 708) embodying any one or more of themethodologies or functions described and/or claimed herein. The logic708, or a portion thereof, may also reside, completely or at leastpartially within the processor 702 during execution thereof by themobile computing and/or communication system 700. As such, the memory704 and the processor 702 may also constitute machine-readable media.The logic 708, or a portion thereof, may also be configured asprocessing logic or logic, at least a portion of which is partiallyimplemented in hardware. The logic 708, or a portion thereof, mayfurther be transmitted or received over a network 714 via the networkinterface 712. While the machine-readable medium of an exampleembodiment can be a single medium, the term “machine-readable medium”should be taken to include a single non-transitory medium or multiplenon-transitory media (e.g., a centralized or distributed database,and/or associated caches and computing systems) that store the one ormore sets of instructions. The term “machine-readable medium” can alsobe taken to include any non-transitory medium that is capable ofstoring, encoding or carrying a set of instructions for execution by themachine and that cause the machine to perform any one or more of themethodologies of the various embodiments, or that is capable of storing,encoding or carrying data structures utilized by or associated with sucha set of instructions. The term “machine-readable medium” canaccordingly be taken to include, but not be limited to, solid-statememories, optical media, and magnetic media.

The Abstract of the Disclosure is provided to allow the reader toquickly ascertain the nature of the technical disclosure. It issubmitted with the understanding that it will not be used to interpretor limit the scope or meaning of the claims. In addition, in theforegoing Detailed Description, it can be seen that various features aregrouped together in a single embodiment for the purpose of streamliningthe disclosure. This method of disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter lies in less than allfeatures of a single disclosed embodiment. Thus, the following claimsare incorporated into the Detailed Description, with each claim standingon its own as a separate embodiment.

What is claimed is:
 1. A system comprising: a data processor; and anadaptive cruise control module, executable by the data processor, beingconfigured to: receive input object data from a subsystem of a hostvehicle, the input object data including distance data and velocity datarelative to detected target vehicles; detect the presence of any targetvehicles within a sensitive zone proximate to the host vehicle based onthe input object data; determine a relative speed and a separationdistance between each of the detected target vehicles relative to thehost vehicle; and generate a velocity command to adjust a speed of thehost vehicle based on the relative speeds and separation distancesbetween the host vehicle and the detected target vehicles to maintain aseparation distance between the host vehicle and the target vehicles,wherein the velocity command is further based on a speed of each of thedetected target vehicles, the relative speed between the host vehicleand each of the detected target vehicles, and the separation distancebetween the host vehicle and each of the detected target vehicles. 2.The system of claim 1 wherein the input object data includes image froma camera and distance data from one or more light imaging, detection,and ranging (LIDAR) sensors.
 3. The system of claim 1 wherein thesensitive zone is a region around the host vehicle within pre-defineddistance thresholds, the pre-defined distance thresholds being definedseparately for an area in front of the host vehicle, an area to the leftof the host vehicle, and an area to the right of the host vehicle,wherein the pre-defined distance threshold for the area in front of thehost vehicle is greater than the pre-defined distance threshold for thearea to the left of the host vehicle and greater than the pre-defineddistance threshold for the area to the right of the host vehicle.
 4. Thesystem of claim 1, wherein the system is configured to cause the hostvehicle to stay out of any blind sports of the target vehicles based onrelative speeds and separation distances between the host vehicle andthe target vehicles.
 5. The system of claim 1 being further configuredto: compute differentials (Δd) of separation distances between the eachof the target vehicles and the host vehicle over time; and to computedifferentials (Δv) of speeds of the target vehicles relative to the hostvehicle over time.
 6. The system of claim 5 being further configured tocompute a predicted position and speed of the target vehicles at afuture point in time.
 7. The system of claim 6 being further configuredto determine whether the predicted position of the target vehicles willencroach a pre-defined safety boundary around the host vehicle.
 8. Thesystem of claim 1 being further configured to direct a vehicle controlsubsystem of the host vehicle to cause the host vehicle to achieve aspeed corresponding to the velocity command.
 9. A method comprising:receiving input object data from a subsystem of a host vehicle, theinput object data including distance data and velocity data relative todetected target vehicles; detecting the presence of any target vehicleswithin a sensitive zone proximate to the host vehicle; determining arelative speed and a separation distance between each of the detectedtarget vehicles relative to the host vehicle; and generating a velocitycommand to adjust a speed of the host vehicle based on the relativespeeds and separation distances between the host vehicle and thedetected target vehicles to maintain a safe separation between the hostvehicle and the target vehicles, wherein the velocity command is basedon relative speeds and relative separation distances between the hostvehicle and the target vehicles.
 10. The method of claim 9 wherein theinput object data includes distance data from one or more light imaging,detection, and ranging (LIDAR) sensors.
 11. The method of claim 9wherein the sensitive zone is a region around the host vehicle withinpre-defined distance thresholds, the pre-defined distance thresholdsbeing defined separately for an area in front of the host vehicle, anarea to the left of the host vehicle, and an area to the right of thehost vehicle.
 12. The method of claim 11 wherein the pre-defineddistance threshold for the area in front of the host vehicle is greaterthan the pre-defined distance threshold for the area to the left of thehost vehicle and greater than the pre-defined distance threshold for thearea to the right of the host vehicle.
 13. The method of claim 9including computing differentials (Δd) of separation distances betweenthe each of the target vehicles and the host vehicle over time.
 14. Themethod of claim 9 including computing differentials (Δv) of speeds ofthe target vehicles relative to the host vehicle over time.
 15. Themethod of claim 9 including computing a predicted position and speed ofthe target vehicles at a future point in time.
 16. A non-transitorymachine-useable storage medium embodying instructions which, whenexecuted by a machine, cause the machine to: receive input object datafrom a subsystem of a host vehicle, the input object data includingimage data from a video stream generated by an image generating device;identify a lead vehicle in the image data as a vehicle object; generatea weighted distance differential corresponding to a weighted differencebetween an actual distance between the host vehicle and the lead vehicleand a desired distance between the host vehicle and the lead vehicle;generate a weighted velocity differential corresponding to a weighteddifference between a velocity of the host vehicle and a velocity of thelead vehicle; combine the weighted distance differential and theweighted velocity differential with the velocity of the lead vehicle toproduce a velocity command for the host vehicle; and adjust the velocitycommand using a dynamic gain, the dynamic gain being a function of: themeasured speed of the host vehicle; an acceleration command; or ameasured acceleration of the host vehicle.
 17. The non-transitorymachine-useable storage medium of claim 16 wherein the input object dataincludes distance data from one or more light imaging, detection, andranging (LIDAR) sensors.
 18. The non-transitory machine-useable storagemedium of claim 16 wherein the instructions further cause the machine toprovide the velocity command to an in-vehicle control system of the hostvehicle, the in-vehicle control system configured to accept the velocitycommand and control a speed of the host vehicle.
 19. The non-transitorymachine-useable storage medium of claim 16, wherein the dynamic gain isa function of the measured acceleration of the host vehicle.
 20. Asystem comprising: an autonomous vehicle; and an adaptive cruise controlmodule comprising the non-transitory machine-useable storage medium ofclaim 16, the adaptive cruise control module being an in-vehiclecomponent of the autonomous vehicle, wherein the autonomous vehicle isthe host vehicle.